Appropriateness of tool usage for evidence critical appraisal: A meta-epidemiological study of 20,000 PROSPERO records of non-Cochrane systematic reviews

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### packages ----------
library("tidyverse")

── Attaching packages ────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.0.0     ✔ purrr   0.2.5
✔ tibble  1.4.2     ✔ dplyr   0.7.6
✔ tidyr   0.8.0     ✔ stringr 1.3.1
✔ readr   1.1.1     ✔ forcats 0.3.0
── Conflicts ───────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

library("stringr")

dataset_PROSPERO2_final<-dataset_PROSPERO2_final %>% 
  mutate(Topic_gral=recode(Topic, c("cancer" = "Cancer")))

Error in mutate_impl(.data, dots) : 
  Evaluation error: Argument 2 must be named, not unnamed.

####  extraer CRDs del campo Citation con regex
prosperoID<-"[C][R][D]([0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9])"
dataset_raw$crds<-str_extract(dataset_raw$Citation, prosperoID)

curated_dataset<-read.csv(file="dataset_PROSPERO2_final.csv")

Error in read.table(file = file, header = header, sep = sep, quote = quote,  : 
  more columns than column names

#### Collaborative Countries
#### no parece muy diferente al plot con unique!!!!  :-(
collaborative_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
  #filter(., unique_country=="unique") %>%
  filter(., tool!="No") %>%
  filter(., new_unitofanalysis!="No") %>%
  filter(., measure!="BMJ Critical Appraisal Tools") %>%
  filter(., measure!="CEBM Critical Appraisal Tools") %>%
  filter(., measure!="JBI Critical Appraisal Tools") %>%
  filter(., measure!="SIGN...SIGN.50 Critical Appraisal Tools")
collaborative_curated_dataset_and_tools<-collaborative_curated_dataset_and_tools %>%
  mutate(new_unitofanalysis = fct_relevel(new_unitofanalysis, "Critical Appraisal of Clinical Practice Guidelines", "Critical Appraisal of Systematic Reviews", "Diagnostic Accuracy Studies","Economic Evaluation Studies","Health education and health behavior research studies", "RCTs", "Non-RCTs and Observational Studies", "RCTs and Observational Studies", "Quantitative Research (Public Health Research)", "Qualitative research studies", "Patient-Reported Outcome Measures Studies", "Mixed methods studies", "Medical education","BMJ Critical Appraisal Tools" ,"CEBM Critical Appraisal Tools","JBI Critical Appraisal Tools","SIGN...SIGN.50 Critical Appraisal Tools"))

Unknown levels in `f`: Health education and health behavior research studies, Quantitative Research (Public Health Research)

ggplot(na.omit(collaborative_curated_dataset_and_tools[,c(1,3:6,13,14,21,24,25)]),aes(x=Topics_general,y=tool, fill=new_unitofanalysis, color=new_unitofanalysis, shape=measure, alpha=Freq_topics)) + 
  geom_count(aes(x=Topics_general,y=tool, fill=new_unitofanalysis,  color=new_unitofanalysis,   shape=measure,alpha=Freq_topics))+
  scale_shape(name = "Assessment objective")+
  scale_shape_manual(values=c(24,21,22,25))+
  coord_flip()+
  theme(axis.text.y=element_text(angle=0, size=6))+
  theme(axis.text.x=element_text(angle=90, size=6, hjust=1))+
  facet_wrap(~measure)+
  theme(legend.position="none")

Scale for 'shape' is already present. Adding another scale for 'shape', which will replace the existing scale.

#### barplots 
#### topic X measure AND unitOfAnalisys
#### UNIQUE COUNTRIES
unique_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
  filter(., unique_country=="unique") %>%
  filter(., tool!="No") %>%
  filter(., new_unitofanalysis!="No") %>%
  filter(., measure!="Diagnostic Accuracy") %>%
  filter(., measure!="BMJ Critical Appraisal Tools") %>%
  filter(., measure!="CEBM Critical Appraisal Tools") %>%
  filter(., measure!="JBI Critical Appraisal Tools") %>%
  filter(., measure!="SIGN...SIGN.50 Critical Appraisal Tools")
unique_curated_dataset_and_tools<-unique_curated_dataset_and_tools %>%
  mutate(new_unitofanalysis = fct_relevel(new_unitofanalysis, "Critical Appraisal of Clinical Practice Guidelines", "Critical Appraisal of Systematic Reviews", "Diagnostic Accuracy Studies","Economic Evaluation Studies","Health education and health behavior research studies", "RCTs", "Non-RCTs and Observational Studies", "RCTs and Observational Studies", "Quantitative Research (Public Health Research)", "Qualitative research studies", "Patient-Reported Outcome Measures Studies", "Mixed methods studies", "Medical education","BMJ Critical Appraisal Tools" ,"CEBM Critical Appraisal Tools","JBI Critical Appraisal Tools","SIGN...SIGN.50 Critical Appraisal Tools"))

Unknown levels in `f`: Health education and health behavior research studies, Quantitative Research (Public Health Research)

ggplot(na.omit(unique_curated_dataset_and_tools[,c(1,3:6,13,14,21,24,25)]),aes(x=Topics_general,fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics)) + 
  geom_bar(stat='count', aes(x=Topics_general,fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics))+
  scale_color_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  scale_fill_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  coord_flip()+
  theme(axis.text.x=element_text(size=6))+
  theme(axis.text.y=element_text(size=10))+
  facet_wrap(~measure)+
  theme(legend.position="none")

#### COLLABORATIVE COUNTRIES
# unique_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
collaborative_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
  filter(str_detect(PROSPERO_country, ',')) %>%
  filter(., tool!="No") %>%
  filter(., new_unitofanalysis!="No") %>%
  filter(., measure!="Diagnostic Accuracy") %>%
  filter(., measure!="BMJ Critical Appraisal Tools") %>%
  filter(., measure!="CEBM Critical Appraisal Tools") %>%
  filter(., measure!="JBI Critical Appraisal Tools") %>%
  filter(., measure!="SIGN...SIGN.50 Critical Appraisal Tools")
collaborative_curated_dataset_and_tools<-collaborative_curated_dataset_and_tools %>%
  mutate(new_unitofanalysis = fct_relevel(new_unitofanalysis, "Critical Appraisal of Clinical Practice Guidelines", "Critical Appraisal of Systematic Reviews", "Diagnostic Accuracy Studies","Economic Evaluation Studies","Health education and health behavior research studies", "RCTs", "Non-RCTs and Observational Studies", "RCTs and Observational Studies", "Quantitative Research (Public Health Research)", "Qualitative research studies", "Patient-Reported Outcome Measures Studies", "Mixed methods studies", "Medical education","BMJ Critical Appraisal Tools" ,"CEBM Critical Appraisal Tools","JBI Critical Appraisal Tools","SIGN...SIGN.50 Critical Appraisal Tools"))

Unknown levels in `f`: Health education and health behavior research studies, Quantitative Research (Public Health Research)

ggplot(na.omit(collaborative_curated_dataset_and_tools[,c(1,3:6,13,14,21,24,25)]),aes(x=Topics_general,fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics)) + 
  geom_bar(stat='count', aes(x=Topics_general,fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics, drop = FALSE))+
  scale_color_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  scale_fill_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  coord_flip()+
  scale_y_continuous(limits = c(0, 500))+
  theme(axis.text.x=element_text(size=6))+
  theme(axis.text.y=element_text(size=10))+
  facet_wrap(~measure)+
  theme(legend.position="none")

Ignoring unknown aesthetics: drop

#### barplots 
#### topic X measure AND unitOfAnalisys
#### UNIQUE COUNTRIES
unique_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
  filter(., unique_country=="unique") %>%
  filter(., tool!="No") %>%
  filter(., new_unitofanalysis!="No") %>%
  filter(., measure!="Diagnostic Accuracy") %>%
  filter(., measure!="BMJ Critical Appraisal Tools") %>%
  filter(., measure!="CEBM Critical Appraisal Tools") %>%
  filter(., measure!="JBI Critical Appraisal Tools") %>%
  filter(., measure!="SIGN...SIGN.50 Critical Appraisal Tools")
unique_curated_dataset_and_tools<-unique_curated_dataset_and_tools %>%
  mutate(new_unitofanalysis = fct_relevel(new_unitofanalysis, "Critical Appraisal of Clinical Practice Guidelines", "Critical Appraisal of Systematic Reviews", "Diagnostic Accuracy Studies","Economic Evaluation Studies","Health education and health behavior research studies", "RCTs", "Non-RCTs and Observational Studies", "RCTs and Observational Studies", "Quantitative Research (Public Health Research)", "Qualitative research studies", "Patient-Reported Outcome Measures Studies", "Mixed methods studies", "Medical education","BMJ Critical Appraisal Tools" ,"CEBM Critical Appraisal Tools","JBI Critical Appraisal Tools","SIGN...SIGN.50 Critical Appraisal Tools"))

Unknown levels in `f`: Health education and health behavior research studies, Quantitative Research (Public Health Research)

ggplot(na.omit(unique_curated_dataset_and_tools[,c(1,3:6,13,14,21,24,25)]),aes(x=as.factor(ALL_year),fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics)) + 
  geom_bar(stat='count', aes(x=as.factor(ALL_year),fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics))+
  scale_color_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  scale_fill_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  #coord_flip()+
  theme(axis.text.x=element_text(size=6))+
  theme(axis.text.y=element_text(size=6))+
  scale_x_discrete(labels = c("2011", "2012", "2013", "2014", "2015", "2016", "2017"))+
  facet_wrap(~measure)+
  theme(legend.position="none")

#### COLLABORATIVE COUNTRIES
# unique_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
collaborative_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
  filter(str_detect(PROSPERO_country, ',')) %>%
  filter(., tool!="No") %>%
  filter(., new_unitofanalysis!="No") %>%
  filter(., measure!="Diagnostic Accuracy") %>%
  filter(., measure!="BMJ Critical Appraisal Tools") %>%
  filter(., measure!="CEBM Critical Appraisal Tools") %>%
  filter(., measure!="JBI Critical Appraisal Tools") %>%
  filter(., measure!="SIGN...SIGN.50 Critical Appraisal Tools")
collaborative_curated_dataset_and_tools<-collaborative_curated_dataset_and_tools %>%
  mutate(new_unitofanalysis = fct_relevel(new_unitofanalysis, "Critical Appraisal of Clinical Practice Guidelines", "Critical Appraisal of Systematic Reviews", "Diagnostic Accuracy Studies","Economic Evaluation Studies","Health education and health behavior research studies", "RCTs", "Non-RCTs and Observational Studies", "RCTs and Observational Studies", "Quantitative Research (Public Health Research)", "Qualitative research studies", "Patient-Reported Outcome Measures Studies", "Mixed methods studies", "Medical education","BMJ Critical Appraisal Tools" ,"CEBM Critical Appraisal Tools","JBI Critical Appraisal Tools","SIGN...SIGN.50 Critical Appraisal Tools"))

Unknown levels in `f`: Health education and health behavior research studies, Quantitative Research (Public Health Research)

ggplot(na.omit(collaborative_curated_dataset_and_tools[,c(1,3:6,13,14,21,24,25)]),aes(x=as.factor(ALL_year),fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics)) + 
  geom_bar(stat='count', aes(x=as.factor(ALL_year),fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics))+
  scale_color_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  scale_fill_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  #coord_flip()+
  theme(axis.text.x=element_text(size=6))+
  theme(axis.text.y=element_text(size=6))+
  scale_x_discrete(labels = c("2011", "2012", "2013", "2014", "2015", "2016", "2017"))+
  facet_wrap(~measure)+
  theme(legend.position="none")

#### barplots 
#### topic X measure AND unitOfAnalisys
#### UNIQUE COUNTRIES
unique_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
  filter(., unique_country=="unique") %>%
  filter(., tool!="No") %>%
  filter(., new_unitofanalysis!="No") %>%
  filter(., measure!="Diagnostic Accuracy") %>%
  filter(., measure!="BMJ Critical Appraisal Tools") %>%
  filter(., measure!="CEBM Critical Appraisal Tools") %>%
  filter(., measure!="JBI Critical Appraisal Tools") %>%
  filter(., measure!="SIGN...SIGN.50 Critical Appraisal Tools")

unique_curated_dataset_and_tools<-unique_curated_dataset_and_tools %>%
  mutate(new_unitofanalysis = fct_relevel(new_unitofanalysis, "Critical Appraisal of Clinical Practice Guidelines", "Critical Appraisal of Systematic Reviews", "Diagnostic Accuracy Studies","Economic Evaluation Studies","Health education and health behavior research studies", "RCTs", "Non-RCTs and Observational Studies", "RCTs and Observational Studies", "Quantitative Research (Public Health Research)", "Qualitative research studies", "Patient-Reported Outcome Measures Studies", "Mixed methods studies", "Medical education","BMJ Critical Appraisal Tools" ,"CEBM Critical Appraisal Tools","JBI Critical Appraisal Tools","SIGN...SIGN.50 Critical Appraisal Tools"))

ggplot(na.omit(unique_curated_dataset_and_tools[,c(1,3:6,13,14,21,24,25)]),aes(x=measure,fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics)) + 
  geom_bar(stat='count', aes(x=measure,fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics))+
  scale_color_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  scale_fill_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  #coord_flip()+
  theme(axis.text.x=element_text(size=6))+
  theme(axis.text.y=element_text(size=6))+
  facet_wrap(~group)+
  theme(legend.position="none")


#### COLLABORATIVE COUNTRIES
# unique_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
collaborative_curated_dataset_and_tools<-curated_dataset_and_tools %>% 
  filter(str_detect(PROSPERO_country, ',')) %>%
  filter(., tool!="No") %>%
  filter(., new_unitofanalysis!="No") %>%
  filter(., measure!="Diagnostic Accuracy") %>%
  filter(., measure!="BMJ Critical Appraisal Tools") %>%
  filter(., measure!="CEBM Critical Appraisal Tools") %>%
  filter(., measure!="JBI Critical Appraisal Tools") %>%
  filter(., measure!="SIGN...SIGN.50 Critical Appraisal Tools")

collaborative_curated_dataset_and_tools<-collaborative_curated_dataset_and_tools %>%
  mutate(new_unitofanalysis = fct_relevel(new_unitofanalysis, "Critical Appraisal of Clinical Practice Guidelines", "Critical Appraisal of Systematic Reviews", "Diagnostic Accuracy Studies","Economic Evaluation Studies","Health education and health behavior research studies", "RCTs", "Non-RCTs and Observational Studies", "RCTs and Observational Studies", "Quantitative Research (Public Health Research)", "Qualitative research studies", "Patient-Reported Outcome Measures Studies", "Mixed methods studies", "Medical education","BMJ Critical Appraisal Tools" ,"CEBM Critical Appraisal Tools","JBI Critical Appraisal Tools","SIGN...SIGN.50 Critical Appraisal Tools"))


ggplot(na.omit(collaborative_curated_dataset_and_tools[,c(1,3:6,13,14,21,24,25)]),aes(x=as.factor(ALL_year),fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics)) + 
  geom_bar(stat='count', aes(x=as.factor(ALL_year),fill=new_unitofanalysis, color=new_unitofanalysis, alpha=Freq_topics))+
  scale_color_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  scale_fill_manual(values=c("#838B8B", "#C1CDCD", "#F0E68C", "#FF8C00", "#1874CD", "#00BFFF", "#458B74", "#66CDAA", "#B4EEB4", "#8B7355", "#CDAA7D", "#FFD39B", "#F5F5DC"))+
  #coord_flip()+
  theme(axis.text.x=element_text(size=6))+
  theme(axis.text.y=element_text(size=6))+
  scale_x_discrete(labels = c("2011", "2012", "2013", "2014", "2015", "2016", "2017"))+
  facet_wrap(~measure)+
  theme(legend.position="none")

### rank comare between continents
my_theme <- function() {
  
  # Colors
  color.background = "white"
  color.text = "#22211d"
  
  # Begin construction of chart
  theme_bw(base_size=15) +
    
    # Format background colors
    theme(panel.background = element_rect(fill=color.background, color=color.background)) +
    theme(plot.background  = element_rect(fill=color.background, color=color.background)) +
    theme(panel.border     = element_rect(color=color.background)) +
    theme(strip.background = element_rect(fill=color.background, color=color.background)) +
    
    # Format the grid
    theme(panel.grid.major.y = element_blank()) +
    theme(panel.grid.minor.y = element_blank()) +
    theme(axis.ticks       = element_blank()) +
    
    # Format the legend
    theme(legend.position = "none") +
    
    # Format title and axis labels
    theme(plot.title       = element_text(color=color.text, size=20, face = "bold")) +
    theme(axis.title.x     = element_text(size=14, color="black", face = "bold")) +
    theme(axis.title.y     = element_text(size=14, color="black", face = "bold", vjust=1.25)) +
    theme(axis.text.x      = element_text(size=10, vjust=0.5, hjust=0.5, color = color.text)) +
    theme(axis.text.y      = element_text(size=10, color = color.text)) +
    theme(strip.text       = element_text(face = "bold")) +
    
    # Plot margins
    theme(plot.margin = unit(c(0.35, 0.2, 0.3, 0.35), "cm"))
}
labels<-as.vector(levels(rank_data$disease))
rank_compare<-read.csv2(file="rank_compare.csv")
rank_data <- rank_compare %>% gather(continent,Rank,-disease)
ggplotColors <- function(g){
  d <- 360/g
  h <- cumsum(c(15, rep(d,g - 1)))
  hcl(h = h, c = 100, l = 65)
}

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